Video transcoder with spatial resolution reduction

ABSTRACT

A method transcodes groups of macroblocks of a partially decoded input bitstream. The groups of macroblocks include intra-mode and inter-mode macroblocks. Each macroblock includes DCT coefficients, and at least one motion vector. The modes of each group of macroblocks are mapped to be identical only if there is an inter-mode block and an intra-mode macroblock in the group. If any of the macroblocks in the group are mapped, then the DCT coefficients and the motion vector for such mapped macroblocks are modified in accordance with the mapping to generate reduced-resolution macroblock for an output compressed bitstream to compensate for drift.

FIELD OF THE INVENTION

This invention relates generally to the field of transcoding bitstreams,and more particularly to reducing spatial resolution while transcodingvideo bitstreams.

BACKGROUND OF THE INVENTION

Video compression enables the storing, transmitting, and processing ofvisual information with fewer storage, network, and processor resources.The most widely used video compression standards include MPEG-1 forstorage and retrieval of moving pictures, MPEG-2 for digital television,and H.263 for video conferencing, see ISO/IEC 11172-2:1993, “InformationTechnology—Coding of Moving Pictures and Associated Audio for DigitalStorage Media up to about 1.5 Mbit/s—Part 2: Video,” D. LeGall, “MPEG: AVideo Compression Standard for Multimedia Applications,” Communicationsof the ACM, Vol. 34, No. 4, pp. 46-58, 1991, ISO/IEC 13818-2:1996,“Information Technology—Generic Coding of Moving Pictures and AssociatedAudio Information—Part 2: Video,” 1994, ITU-T SG XV, DRAFT H.263, “VideoCoding for Low Bitrate Communication,” 1996, ITU-T SG XVI, DRAFT13H.263+Q15-A-60 rev.0, “Video Coding for Low Bitrate Communication,”1997.

These standards are relatively low-level specifications that primarilydeal with a spatial compression of images or frames, and the spatial andtemporal compression of sequences of frames. As a common feature, thesestandards perform compression on a per frame basis. With thesestandards, one can achieve high compression ratios for a wide range ofapplications.

Newer video coding standards, such as MPEG-4 for multimediaapplications, see ISO/IEC 14496-2:1999, “Information technology—codingof audio/visual objects, Part 2: Visual,” allow arbitrary-shaped objectsto be encoded and decoded as separate video object planes (VOP). Theobjects can be visual, audio, natural, synthetic, primitive, compound,or combinations thereof. Also, there is a significant amount of errorresilience features built into this standard to allow for robusttransmission across error-prone channels, such as wireless channels.

The emerging MPEG-4 standard is intended to enable multimediaapplications, such as interactive video, where natural and syntheticmaterials are integrated, and where access is universal. In the contextof video transmission, these compression standards are needed to reducethe amount of bandwidth on networks. The networks can be wireless or theInternet. In any case, the network has limited capacity, and contentionfor scarce resources should be minimized.

A great deal of effort has been placed on systems and methods thatenable devices to transmit the content robustly and to adapt the qualityof the content to the available network resources. When the content isencoded, it is sometimes necessary to further decode the bitstreambefore it can be transmitted through the network at a lower bit-rate orresolution.

As shown in FIG. 1, this can be accomplished by a transcoder 100. In asimplest implementation, the transcoder 100 includes a cascaded decoder110 and encoder 120. A compressed input bitstream 101 is fully decodedat an input bit-rate R_(in), then encoded at an output bit-rate R_(out)102 to produce the output bitstream 103. Usually, the output rate islower than the input rate. In practice, full decoding and full encodingin a transcoder is not done due to the high complexity of encoding thedecoded bitstream.

Earlier work on MPEG-2 transcoding has been published by Sun et al., in“Architectures for MPEG compressed bitstream scaling,” IEEE Transactionson Circuits and Systems for Video Technology, April 1996. There, fourmethods of rate reduction, with varying complexity and architecture,were described.

FIG. 2 shows a first example method 200, which is referred to as anopen-loop architecture. In this architecture, the input bitstream 201 isonly partially decoded. More specifically, macroblocks of the inputbitstream are variable-length decoded (VLD) 210 and inverse quantized220 with a fine quantizer Q₁, to yield discrete cosine transform (DCT)coefficients. Given the desired output bit-rate 202, the DCT blocks area re-quantized by a coarser level quantizer Q₂ of the quantizer 230.These re-quantized blocks are then variable-length coded (VLC) 240, anda new output bitstream 203 at a lower rate is formed. This scheme ismuch simpler than the scheme shown in FIG. 1 because the motion vectorsare re-used and an inverse DCT operation is not needed. Note, here thechoice of Q₁ and Q₂ strictly depend on rate characteristics of thebitstream. Other factors, such as possibly, spatial characteristics ofthe bitstream are not considered.

FIG. 3 shows a second example method 300. This method is referred to asa closed-loop architecture. In this method, the input video bitstream isagain partially decoded, i.e., macroblocks of the input bitstream arevariable-length decoded (VLD) 310, and inverse quantized 320 with Q₁ toyield discrete cosine transform (DCT) coefficients 321. In contrast tothe first example method described above, correction DCT coefficients332 are added 330 to the incoming DCT coefficients 321 to compensate forthe mismatch produced by re-quantization. This correction improves thequality of the reference frames that will eventually be used fordecoding. After the correction has been added, the newly formed blocksare re-quantized 340 with Q₂ to satisfy a new rate, and variable-lengthcoded 350, as before. Note, again Q₁ and Q₂ are rate based.

To obtain the correction component 332, the re-quantized DCTcoefficients are inverse quantized 360 and subtracted 370 from theoriginal partially decoded DCT coefficients. This difference istransformed to the spatial domain via an I inverse DCT (IDCT) 365 andstored into a frame memory 380. The motion vectors 381 associated witheach incoming block are then used to recall the corresponding differenceblocks, such as in motion compensation 290. The corresponding blocks arethen transformed via the DCT 332 to yield the correction component. Aderivation of the method shown in FIG. 3 is described in “A frequencydomain video transcoder for dynamic bit-rate reduction of MPEG-2bitstreams,” by Assuncao et al., IEEE Transactions on Circuits andSystems for Video Technology, pp. 953-957, 1998.

Assuncao et al. also described an alternate method for the same task. Inthe alternative method, they used a motion compensation (MC) loopoperating in the frequency domain for drift compensation. Approximatematrices were derived for fast computation of the MC blocks in thefrequency domain. A Lagrangian optimization was used to calculate thebest quantizer scales for transcoding. That alternative method removedthe need for the IDCT/DCT components.

According to prior art compression standards, the number of bitsallocated for encoding texture information is controlled by aquantization parameter (QP). The above methods are similar in thatchanging the QP based on information that is contained in the originalbitstream reduces the rate of texture bits. For an efficientimplementation, the information is usually extracted directly from thecompressed domain and can include measures that relate to the motion ofmacroblocks or residual energy of DCT blocks. The methods describesabove are only applicable for bit-rate reduction.

Besides bit-rate reduction, other types of transformation of thebitstream can also be performed. For example, object-basedtransformations have been described in U.S. patent application Ser. No.09/504,323, “Object-Based Bitstream Transcoder,” filed on Feb. 14, 2000by Vetro et al. Transformations on the spatial resolution have beendescribed in “Heterogeneous video transcoding to lower spatio-temporalresolutions, and different encoding formats,” IEEE Transaction onMultimedia, June 2000, by Shanableh and Ghanbari.

It should be noted these methods produce bitstreams at a reduced spatialresolution reduction that lack quality, or are accomplished with highcomplexity. Also, proper consideration has not been given to the meansby which reconstructed macroblocks are formed. This can impact both thequality and complexity, and is especially important when consideringreduction factors different than two. Moreover, these methods do notspecify any architectural details. Most of the attention is spent onvarious means of scaling motion vectors by a factor of two.

FIG. 4 shows the details of a method 400 for transcoding an inputbitstream to an output bitstream 402 at a lower spatial resolution. Thismethod is an extension of the method shown in FIG. 1, but with thedetails of the decoder 110 and encoder 120 shown, and a down-samplingblock 410 between the decoding and encoding processes. The decoder 110performs a partial decoding of the bitstream. The down-sampler reducesthe spatial resolution of groups of partially macroblocks. Motioncompensation 420 in the decoder uses the full-resolution motion vectorsmv_(f) 421, while motion compensation 430 in the encoder useslow-resolution motion vectors mv_(r) 431. The low-resolution motionvectors are either estimated from the down-sampled spatial domain framesy_(n) ¹ 403, or mapped from the full-resolution motion vectors. Furtherdetail of the transcoder 400 are described below.

FIG. 5 shows the details of an open-loop method 500 for transcoding aninput bitstream 501 to an output bitstream 502 at a lower spatialresolution. In this method, the video bitstream is again partiallydecoded, i.e., macroblocks of the input bitstream are variable-lengthdecoded (VLD) 510 and inverse quantized 520 to yield discrete cosinetransform (DCT) coefficients, these steps are well known.

The DCT macroblocks are then down-sampled 530 by a factor of two bymasking the high frequency coefficients of each 8×8 (2³×2³)luminanceblock in the 16×16 (2⁴×2⁴) macroblock to yield four 4×4 DCT blocks, seeU.S. Pat. No. 5,262,854, “Low-resolution HDTV receivers,” issued to Ngon Nov. 16, 1993. In other words, down-sampling turns a group of blocks,for example four, into a group of four blocks of a smaller size.

By performing down-sampling in the transcoder, the transcoder must takeadditional steps to re-form a compliant 16×16 macroblock, which involvestransformation back to the spatial domain, then again to the DCT domain.After the down-sampling, blocks are re-quantized 540 using the samequantization level, and then variable length coded 550. No methods havebeen described to perform rate control on the reduced resolution blocks.

To perform motion vector mapping 560 from full 559 to reduced 561 motionvectors, several methods suitable for frame-based motion vectors havebeen described in the prior art. To map from four frame-based motionvectors, i.e., one for each macroblock in a group, to one motion vectorfor the newly formed 16×16 macroblock, simple averaging or medianfilters can be applied. This is referred to as a 4:1 mapping.

However, certain compression standards, such as MPEG-4 and H.263,support advanced prediction modes that allow one motion vector per 8×8block. In this case, each motion vector is mapped from a 16×16macroblock in the original resolution to an 8×8 block in the reducedresolution macroblock. This is referred to as a 1:1 mapping.

FIG. 6 shows possible mappings 600 of motion vector from a group of four16×16 macroblocks 601 to either one 16×16 macroblock 602 or four 8×8macroblocks 603. It is inefficient to always use the 1:1 mapping becausemore bits are used to code four motion vectors. Also, in general, theextension to field-based motion vectors for interlaced images isnon-trivial. Given the down-sampled DCT coefficients and mapped motionvectors, the data are subject to variable length coding and the reducedresolution bitstream can be formed as is well known.

It is desired to provide a method for transcoding bitstreams thatovercomes the problems of the prior art methods for spatial resolutionreduction. Furthermore, it is desired to provide a balance betweencomplexity and quality in the transcoder. Furthermore it is desired tocompensate for drift, and provide better up-sampling techniques duringthe transcoding.

SUMMARY OF THE INVENTION

A method up-samples a compressed bitstream. The compressed bitstream ispartially decoding to produce macroblocks. Each macroblock has DCTcoefficients according to a predetermined dimensionality of themacroblock.

DCT filters are applied to the DCT coefficients of each macroblock togenerate up-sampled macroblocks for each macroblock, there is oneup-sampled macroblock generated by each filter. Each generatedup-sampled macroblock has the predetermined dimensionality.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a prior art cascaded transcoder;

FIG. 2 is a block diagram of a prior art open-loop transcoder forbit-rate reduction;

FIG. 3 is a block diagram of a prior art closed-loop transcoder forbit-rate reduction;

FIG. 4 is a block diagram of a prior art cascaded transcoder for spatialresolution reduction;

FIG. 5 is a block diagram of a prior art open-loop transcoder forspatial resolution reduction;

FIG. 6 is a block diagram of prior art motion vector mapping;

FIG. 7 is a block diagram of a first application transcoding a bitstreamto a reduced spatial resolution according to the invention;

FIG. 8 is a block diagram of a second application transcoding abitstream to a reduced spatial resolution according to the invention;

FIG. 9 is a block diagram of an open-loop transcoder for spatialresolution reduction according to the invention;

FIG. 10 is a block diagram of a first closed-loop transcoder for spatialresolution reduction with drift compensation in the reduced resolutionaccording to the invention;

FIG. 11a is a block diagram of a second closed-loop transcoder forspatial resolution reduction with drift compensation in the originalresolution according to the invention;

FIG. 11b is a block diagram of a third closed-loop transcoder forspatial resolution reduction with drift compensation in the originalresolution according to the invention;

FIG. 12 is an example of a group of macroblocks containing macroblockmodes, DCT coefficient data, and corresponding motion vector data;

FIG. 13 is a block diagram of a group of blocks processor according tothe invention;

FIG. 14A is a block diagram of a first method for group of blocksprocessing according to the invention;

FIG. 14B is block diagram of a second method for group of blocksprocessing according to the invention;

FIG. 14C is a block diagram of a third method for a group of blocksprocessing according to the invention;

FIG. 15A illustrates a prior art concept of down-sampling in the DCT orspatial domain;

FIG. 15B is a block diagram of prior art up-sampling in the DCT orspatial domain;

FIG. 15C is a block diagram of up-sampling in the DCT domain accordingto the invention; and

FIG. 16 is a diagram of up-sampling in the DCT domain according to theinvention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Introduction

The invention provides a system and method for transcoding compressedbitstreams of digital video signals to a reduced spatial resolution withminimum drift. First, several applications for content distribution thatcan use the transcoder according to the invention are described. Next,an analysis of a basic method for generating a bitstream at a lowerspatial resolution is provided. Based on this analysis, severalalternatives to the base method and the corresponding architectures thatare associated with each alternative are described.

A first alternative, see FIG. 9, uses an open-loop architecture, whilethe other three alternatives, FIGS. 10 and 11a-b, correspond toclosed-loop architectures that provide a means of compensating driftincurred by down-sampling, re-quantization and motion vector truncation.One of the closed-loop architectures performs this compensation in thereduced resolution, while the others perform this compensation in theoriginal resolution in the DCT domain for better quality.

As will be described in greater detail below, the open-loop architectureof FIG. 9 is of low complexity. There is no reconstruction loop, noDCT/IDCT blocks, no frame store, and the quality is reasonable for lowpicture resolution, and bit-rates. This architecture is suitable forInternet applications and software implementations. The firstclosed-loop architecture of FIG. 10 is also of moderate complexity. Itincludes a reconstruction loop, IDCT/DCT blocks, and a frame store.Here, the quality can be improved with drift compensation in reducedresolution domain. The second closed-loop architecture of FIG. 11a is ofmoderate complexity. It includes a reconstruction loop, IDCT/DCT blocks,and a frame store. The quality can be improved with drift compensationin the original resolution domain, and does require up-sampling of thereduced resolution frames. The third closed loop architecture uses acorrection signal obtained in the reduced resolution domain.

To support the architectures according to the present invention, severaladditional techniques for processing blocks that would otherwise havegroups of macroblock with “mixed” modes at the reduced resolution arealso described.

A group of blocks, e.g., four, to be down-sampled is considered a“mixed” block when the group of blocks to be down-sampled containsblocks coded in both intra- and inter-modes. In the MPEG standardsI-frames contain only macroblocks coded according to the intra-mode, andP-frames can include intra- and inter-mode coded blocks. These modesneed to be respected, particularly while down-sampling, otherwise thequality of the output can be degraded.

Also, methods for drift-compensation and up-sampling DCT based data aredescribed. These methods are useful for the second and third closed-looparchitectures so that operations after the up-sampling can be performedproperly and without additional conversion steps.

Applications for Reduced Spatial Resolution Transcoding

The primary target application for the present invention is thedistribution of digital television (DTV) broadcast and Internet contentto devices with low-resolution displays, such as wireless telephones,pagers, and personal digital assistance. MPEG-2 is currently used as thecompression format for DTV broadcast and DVD recording, and MPEG-1content is available over the Internet.

Because MPEG-4 has been adopted as the compression format for videotransmission over mobile networks, the present invention deals withmethods for transcoding MPEG-1/2 content to lower resolution MPEG-4content.

FIG. 7 shows a first example of a multimedia content distribution system700 that uses the invention. The system 700 includes an adaptive server701 connected to clients 702 via an external network 703. As acharacteristics the clients have small-sized displays or are connectedby low bit-rate channels. Therefore, there is a need to reduce theresolution of any content distributed to the clients 702.

Input source multimedia content 704 is stored in a database 710. Thecontent is subject to a feature extraction and an indexing process 720.A database server 740 allows the clients 702 to browse the content ofthe database 710 and to make requests for specific content. A searchengine 730 can be used to locate multimedia content. After the desiredcontent has been located, the database server 740 forwards themultimedia content to a transcoder 750 according to the invention.

The transcoder 750 reads network and client characteristics. If thespatial resolution of the content is higher than the displaycharacteristics of the client, then the method according to theinvention is used to reduce the resolution of the content to match thedisplay characteristics of the client. Also, if the bit-rate on thenetwork channel is less than the bit-rate of the content, the inventioncan also be used.

FIG. 8 shows a second example of a content distribution system 800. Thesystem 800 includes a local “home” network 801, the external network703, a broadcast network 803, and the adaptive server 701 as describedfor FIG. 7. In this application, high-quality input source content 804can be transported to clients 805 connected to the home network 801 viathe broadcast network 803, e.g., cable, terrestrial or satellite. Thecontent is received by a set-top box or gateway 820 and stored into alocal memory or hard-disk drive (HDD) 830. The received content can bedistributed to the clients 805 within the home. In addition, the contentcan be transcoded 850 to accommodate any clients that do not have thecapability to decode/display the full resolution content. This can bethe case when a high-definition television (HDTV) bitstream is receivedfor a standard-definition television set. Therefore, the content shouldbe transcoded to satisfy client capabilities within the home.

Moreover, if access to the content stored on the HDD 830 is desired by alow-resolution external client 806 via the external network 802, thenthe transcoder 850 can also be used to deliver low-resolution multimediacontent to this client.

Analysis of Base Method

In order to design a transcoder with varying complexity and quality, thesignals generated by the method of FIG. 4 are further described andanalyzed. With regard to notation in the equations, lowercase variablesindicate spatial domain signals, while uppercase variables represent theequivalent signal in the DCT domain. The subscripts on the variablesindicates time, while a superscript equal to one denotes a signal thathas drift and a superscript equal to two denotes a signal that is driftfree. The drift is introduced through lossy processes, such asre-quantization, motion vector truncation or down-sampling. A method fordrift compensation is described below.

I-frames

Because there is no motion compensated prediction for I-frames, i.e.,

x _(n) ¹ =e _(n) ¹,  (1)

the signal is down-sampled 410,

y _(n) ¹ =D(x _(n) ¹).  (2)

Then, in the encoder 120,

g _(n) ² =y _(n) ¹.  (3)

The signal g_(n) ² is subject to the DCT 440, then quantized 450 withquantization parameter Q₂. The quantized signal c_(out) is variablelength coded 460 and written to the transcoded bitstream 402. As part ofthe motion compensation loop in the encoder, c_(out) is inversequantized 470 and subject to the IDCT 480. The reduced resolutionreference signal y_(n) ² 481 is stored into the frame buffer 490 as thereference signal for future frame predictions.

P-frames

In the case of P-frames, the identity

x _(n) ¹ =e _(n) ¹ +M _(f)(x _(n−1) ¹)  (4)

yields the reconstructed full-resolution picture. As with the I-frame,this signal is then down-converted via equation (2). Then, thereduced-resolution residual is generated according to

g _(n) ² =y _(n) ¹ −M _(r)(y _(n−1) ²),  (5)

which is equivalently expressed as,

g _(n) ² =D(e _(n) ¹)+D(x _(n−1) ¹))−M _(r)(y _(n−1) ²).  (6)

The signal given by equation (6) represents the reference signal thatthe architectures described by this invention approximate. It should beemphasized that the complexity in generating this reference signal ishigh and is desired to approximate the quality, while achievingsignificant complexity reduction.

Open-Loop Architecture

Give the approximations,

y _(n−1) ² =y _(n−1) ¹  (7a)

D(M _(f)(x _(n−1) ¹))=M _(r)(D(x _(n−1) ¹))=M _(r)(y _(n−1) ¹)  (7b)

the reduced resolution residual signal in equation (6) is expressed as,

g _(n) ² =D(e _(n) ¹).  (8)

The above equation suggests the open-loop architecture for a transcoder900 as shown in FIG. 9.

In the transcoder 900, the incoming bitstream 901 signal is variablelength decoded 910 to generate inverse quantized DCT coefficients 911,and full resolution motion vectors, mv_(f) 902. The full-resolutionmotion vectors are mapped by the MV mapping 920 to reduced-resolutionmotion vectors, mv_(r) 903. The quantized DCT coefficients 911 areinverse quantized, with quantizer Q₁ 930, to yield signal E_(n) ¹ 931.This signal is then subject to a group of blocks processor 1300 asdescribed in greater detail below. The output of the processor 1300 isdown-sampled 950 to produce signal G² _(n) 951. After down-sampling, thesignal is quantized with quantizer Q₂ 960. Finally, the reducedresolution re-quantized DCT coefficients and motion vectors are variablelength coded 970 and written to the transcoded output bitstream 902.

The details and preferred embodiments of the group of blocks processor1300 are described below, but briefly, the purpose of the group ofblocks processor is to pre-process selected groups of macroblocks toensure that the down-sampling process 950 will not generate groups ofmacroblocks in which its sub-blocks have different coding modes, e.g.,both inter-and intra-blocks. Mixed coding modes within a macroblock arenot supported by any known video coding standards.

Drift Compensation in Reduced Resolution

Given only the approximation given by equation (7b), the reducedresolution residual signal in equation (6) is expressed as,

g _(n) ² =D(e _(n) ¹)+M _(r)(y _(n−1) ¹ −y _(n−1) ²)  (9)

The above equation suggests the closed-loop architecture 1000 shown inFIG. 10, which compensates for drift in the reduced resolution.

In this architecture, the incoming signal 1001 is variable lengthdecoded 1010 to yield quantized DCT coefficients 1011 and fullresolution motion vectors mv_(f) 1012. The full-resolution motionvectors 1012 are mapped by the MV mapping 1020 to yield a set ofreduced-resolution motion vectors, mv_(r) 1021. The quantized DCTcoefficients are inverse quantized 1030, with quantizer Q₁ to yieldsignal E_(n) ¹ 1031. This signal is then subject to the group of blocksprocessor 1300 and down-sampled 1050. After down-sampling 1050, areduced-resolution drift-compensating signal 1051 is added 1060 to thelow-resolution residual 1052 in the DCT domain.

The signal 1061 is quantized with spatial quantizer Q₂ 1070. Finally,the reduced resolution re-quantized DCT coefficients 1071 and motionvectors 1021 are variable length coded 1080 to generate the outputtranscoded bitstream 1002.

The reference frame from which the reduced-resolution drift-compensatingsignal is generated is obtained by an inverse quantization 1090 of there-quantizer residual G² 1071, which is then subtracted 1092 from thedown-sampled residual G_(n) ² 1052. This difference signal is subject tothe IDCT 1094 and added 1095 to the low-resolution predictive component1096 of the previous macroblock stored in the frame store 1091. This newsignal represents the difference (y_(n−1) ¹y_(n−1) ²) 1097 and is usedas the reference for low-resolution motion compensation for the currentblock.

Given the stored reference signal, low-resolution motion compensation1098 is performed and the prediction is subject to the DCT 1099. ThisDCT-domain signal is the reduced-resolution drift-compensating signal1051. This operation is performed on a macroblock-by-macroblock basisusing the set of low-resolution motion vectors, mv_(r) 1021.

First Method of Drift Compensation in Original Resolution

For an approximation,

M _(r)(y _(n−1) ²)=D(M _(f)(U(y _(n−1) ²)))=D(M _(f)(x _(n−1) ²)),  (10)

the reduced resolution residual signal in equation (6) is expressed as,

g _(n) ² =D(e _(n) ¹)+M _(f)(x _(n−1) ¹ −x _(n−1) ²).  (11)

The above equation suggests the closed-loop architecture 1100 shown inFIG. 11, which compensates for drift in the original resolutionbitstream.

In this architecture, the incoming signal 1001 is variable lengthdecoded 1110 to yield quantized DCT coefficients 1111, and fullresolution motion vectors, mv_(f) 1112. The quantized DCT coefficients1111 are inverse quantized 1130, with quantizer Q₁, to yield signalE_(n) ¹ 1131. This signal is then subject to the group of blocksprocessor 1300. After group of blocks processing 1300, anoriginal-resolution drift-compensating signal 1151 is added 1160 to theresidual 1141 in the DCT domain. The signal 1162 is then down-sampled1150, and quantized 1170 with quantizer Q₂. Finally, the reducedresolution re-quantized DCT coefficients 1171, and motion vectors 1121are variable length coded 1180, and written to the transcoded bitstream1102.

The reference frame from which the original-resolutiondrift-compensating signal 1151 is generated by an inverse quantization1190 of the re-quantizer residual G_(n) ² 1171, which is then up-sampled1191. Here, after the up-sampling the up-sampled signal is subtracted1192 from the original resolution residual 1161. This difference signalis subject to the IDCT 1194, and added 1195 to the original-resolutionpredictive component 1196 of the previous macroblock. This new signalrepresents the difference (x_(n−1) ¹−x_(n−1) ²) 1197, and is used as thereference for motion compensation of the current macroblock in theoriginal resolution.

Given the reference signal stored in the frame buffer 1181,original-resolution motion compensation 1198 is performed, and theprediction is subject to the DCT 1199. This DCT-domain signal is theoriginal-resolution drift-compensating signal 1151. This operation isperformed on a macroblock-by-macroblock basis using the set oforiginal-resolution motion vectors, mv_(f) 1121.

Second Method of Drift Compensation in Original Resolution

FIG. 11b shows an alternative embodiment of the closed loop architectureof FIG. 11a. Here, the output of the inverse quantization 1190 of there-quantizer residual G_(n) ² 1172 is subtracted 1192 from the reducedresolution signal before up-sampling 1191.

Both drift compensating architectures in the original resolution do notuse the motion vector approximations in generating the driftcompensating signal 1151. This is accomplished by the use of up-sampling1191. The two alternative architectures mainly differ in the choice ofsignals that are used to generate the difference signal. In the firstmethod, the difference signal represents error due to re-quantizationand resolution conversion, while the difference signal in the secondmethod only considers the error due to re-quantization.

Because the up-sampled signal is not considered in the future decodingof the transcoded bitstream, it is reasonable to exclude any errormeasured by consecutive down-sampling and up-sampling in the driftcompensation signal. However, up-sampling is still employed for tworeasons: to make use of the full-resolution motion vectors 1121 to avoidany further approximation, and so that the drift compensating signal isin the original resolution and can be added 1160 to the incomingresidual 1161 before down-sampling 1150.

Mixed Block Processor

The purpose of the group of blocks processor 1300 is to pre-processselected macroblocks to ensure that the down-sampling process do notgenerate macroblocks in which its sub-blocks have different codingmodes, e.g., inter- and intra-blocks. Mixed coding modes withinmacroblocks are not supported by any known video coding standards.

FIG. 12 shows an example of a group of macroblocks 1201 that can lead toa group of blocks 1202 in the reduced resolution after transcoding 1203.Here, there are three inter-mode blocks, and one intra-mode block. Note,the motion vector (MV) for the intra-mode block is zero. Determiningwhether a particular group of blocks is a mixed group, or not, dependsonly on the macroblock mode. The group of blocks processor 1300considers groups of four macroblocks 1201 that form a single macroblock1202 in the reduced resolution. In other words, for the luminancecomponent, MB(0) 1210 corresponds to sub-block b(0) 1220 in the reducedresolution macroblock 1202, and similarly, MB(1) 1211 will correspond tob(1) 1221, MB(k) 1212 corresponds to b(2) 1222, and MB(k+1) 1213corresponds to b(3) 1223, where k is the number of macroblocks per rowin the original resolution. Chrominance components are handled in asimilar manner that is consistent with luminance modes.

A group of MB modes determine whether the group of blocks processor 1300should process a particular MB. The group of blocks is processed if thegroup contains at least one intra-mode block, and at least oneinter-mode block. After a macroblock is selected, its DCT coefficientsand motion vector data are subject to modification.

FIG. 1300 shows the components of the group of blocks processor 1300.For a selected group of mixed blocks 1301, the group of blocks processorperforms mode mapping 1310, motion vector modification 1320, and DCTcoefficient modification 1330 to produce an output non-mixed block 1302.Given that the group of blocks 1301 has been identified, the modes ofthe macroblocks are modified so that all macroblocks are identical. Thisis done according to a pre-specified strategy to match the modes of eachsub-block in a reduced resolution block.

In accordance with the chosen mode mapping, the MV data are then subjectto modification 1320. Possible modifications that agree withcorresponding mode mappings are described in detail below for FIGS.14A-C. Finally, given both the new MB mode and the MV data, thecorresponding DCT coefficients are also modified 1330 to agree with themapping.

In a first embodiment of the group of blocks processor as shown in FIG.14A, the MB modes of the group of blocks 1301 are modified to beinter-mode by the mode mapping 1310. Therefore, the MV data for theintra-blocks are reset to zero by the motion vector processing, and theDCT coefficients corresponding to intra-blocks are also reset to zero bythe DCT processing 1330. In this way, such sub-blocks that have beenconverted are replicated with data from the corresponding block in thereference frame.

In a second embodiment of the group of blocks processor as shown in FIG.14B, the MB modes of the groups of mixed block are modified to be tointer-mode by the mapping 1310. However, in contrast to the firstpreferred embodiment, the MV data for intra-MB's are predicted. Theprediction is based on the data in neighboring blocks, which can includeboth texture and motion data. Based on this predicted motion vector, anew residual for the modified block is calculated. The final step 1320resets the inter-DCT coefficients to intra-DCT coefficients.

In a third embodiment shown in FIG. 14C, the MB modes of the grouped ofblocks are modified 1310 to intra-mode. In this case, there is no motioninformation associated with the reduced-resolution macroblock, thereforeall associated motion vector data are reset 1320 to zero. This isnecessary to perform in the transcoder because the motion vectors ofneighboring blocks are predicted from the motion of this block. Toensure proper reconstruction in the decoder, the MV data for the groupof blocks must be reset to zero in the transcoder. The final step 1330generates intra-DCT coefficients to replace the inter-DCT coefficients,as above.

It should be noted that to implement the second and third embodimentsdescribed above, a decoding loop that reconstructs to full-resolutioncan be used. This reconstructed data can be used as a reference toconvert the DCT coefficients between intra- and inter-modes, or inter-and intra-modes. However, the use of such a decoding loop is notrequired. Other implementations can perform the conversions within thedrift compensating loops.

For a sequence of frames with a small amount of motion, and a low-levelof detail the low complexity strategy of FIG. 14A can be used.Otherwise, the equally complex strategies of either FIG. 14b or FIG. 14cshould be used. The strategy of FIG. 14c provides the best quality.

Drift Compensation with Block Processing

It should be noted that the group of block processor 1300 can also beused to control or minimize drift. Because intra coded blocks are notsubject to drift, the conversion of inter-coded blocks to intra-codedblocks lessens the impact of drift.

As a first step 1350 of FIG. 14C, the amount of drift in the compressedbitstream is measured. In the closed-loop architectures, the drift canbe measured according to the energy of the difference signal generatedby 1092 and 1192 or the drift compensating signal stored in 1091 and1191. Computing the energy of a signal is a well-known method. Theenergy that is computed accounts for various approximations, includingre-quantization, down-sampling and motion vector truncation.

Another method for computing the drift, which is also applicable toopen-loop architectures, estimates the error incurred by truncatedmotion vectors. It is known that half-pixel motion vectors in theoriginal resolution lead to large reconstruction errors when theresolution is reduced. Full-pixel motion vectors are not subject to sucherrors because they can still be mapped correctly to half-pixellocations. Given this, one possibility to measure the drift is to recordthe percentage of half-pixel motion vectors. However, because the impactof the motion vector approximation depends on the complexity of thecontent, another possibility is that the measured drift be a function ofthe residual components that are associated with blocks havinghalf-pixel motion vectors.

The methods that use the energy of the difference signal and motionvector data to measure drift can be used in combination, and can also beconsidered over sub-regions in the frame. Considering sub-regions in theframe is advantageous because the location of macroblocks that benefitmost by drift compensation method can be identified. To use thesemethods in combination, the drift is measured by the energy of thedifference signal, or drift compensating signal for macroblocks havinghalf-pixel motion vectors in the original resolution.

As a second step, the measured value of drift is translated into an“intra refresh rate” 1351 that is used as input to the group of blocksprocessor 1300. Controlling the percentage of intra-coded blocks hasbeen considered in the prior art for encoding of video forerror-resilient transmission, see for example “Analysis of VideoTransmission over Lossy Channels,” Journal of Selected Areas ofCommunications, by Stuhlmuller, et al, 2000. In that work, aback-channel from the receiver to the encoder is assumed to communicatethe amount of loss incurred by the transmission channel, and theencoding of intra-coded blocks is performed directly from the source toprevent error propagation due to lost data in a predictive codingscheme.

In contrast, the invention generates new intra-blocks in the compresseddomain for an already encoded video, and the conversion from inter- tointra-mode is accomplished by the group of blocks processor 1300.

If the drift exceeds a threshold amount of drift, the group of blocksprocessor 1300 of FIG. 14c is invoked to convert an inter-mode block toan intra-mode block. In this case, the conversion is be performed at afixed and pre-specified intra refresh rate. Alternatively, conversioncan be done at an intra refresh rate that is proportional to the amountof drift measured. Also, rate-distortion characteristics of the signalcan be taken into account to make appropriate trade-offs between theintra refresh rate and quantizers used for coding intra and interblocks.

It should be noted that the invention generates new intra-blocks in thecompressed domain, and this form of drift compensation can be performedin any transcoder with or without resolution reduction.

Down-Sampling

Any down-sampling method can be used by the transcoder according to theinvention. However, the preferred down-sampling method is according toU.S. Pat. No. 5,855,151, “Method and apparatus for down-converting adigital signal,” issued on Nov 10, 1998 to Sun et al, incorporatedherein by reference.

The concept of this down-sampling method is shown in FIG. 15A. A groupincludes four 2^(N)×2^(N) DCT blocks 1501. That is, the size of thegroup is 2^(N+1)×2^(N+1). A “frequency synthesis” or filtering 1510 isapplied to the group of blocks to generate a single 2^(N)×2^(N) DCTblock 1511. From this synthesized block, a down-sampled DCT block 1512can be extracted.

This operation has been described for the DCT domain using 2Doperations, but the operations can also be performed using separable 1Dfilters. Also, the operations can be completely performed in the spatialdomain. Equivalent spatial domain filters can be derived using themethods described in U.S. patent application Ser. No. 09/035,969, “Threelayer scalable decoder and method of decoding,” filed on Mar. 6, 1998 byVetro et al, incorporated herein by reference.

The main advantage of using the down-sampling method in the transcoderaccording to the invention is that correct dimension of sub-blocks inthe macroblock are obtained directly, e.g., from four 8×8 DCT blocks, asingle 8×8 block can be formed. On the other hand, alternate prior artmethods for down-sampling produce down-sampled data in a dimension thatdoes not equal the required dimension of the outgoing sub-block of amacroblock, e.g., from four 8×8 DCT blocks, a four 4×4 DCT blocks isobtained. Then, an additional step is needed to compose a single 8×8 DCTblock.

The above filters are useful components to efficiently implement thearchitecture shown in FIG. 11 that requires up-sampling. More generally,the filters derived here can be applied to any system that requiresarithmetic operations on up-sampled DCT data, with or without resolutionreduction or drift compensation.

Up-Sampling

Any means of prior art up-sampling can be used in the present invention.However, Vetro, et al., in U.S. patent application “Three layer scalabledecoder and method of decoding,” see above, states that the optimalup-sampling method is dependent on the method of down-sampling.Therefore, the use an up-sampling filters x_(u) that corresponds to thedown-sampling filters x_(d) is preferred, where the relation between thetwo filters is given by,

x _(u) =x _(d) ^(T)(x _(d) x _(d) ^(T))⁻¹  (12)

There are two problems associated with the filters derived from theabove equations. First, the filters are only applicable in the spatialdomain filters because the DCT filters are not invertable. But, this isa minor problem because the corresponding spatial domain filters can bederived, then converted to the DCT-domain.

However, the second problem is that the up-sampling filters obtained inthis way correspond to the process shown in FIG. 15B. In this process,for example, an 2^(N)×2^(N) block 1502 is up-sampled 1520 to a single2^(N+1)×2^(N+1) block 1530. If up-sampling is performed entirely in thespatial domain, there is no problem. However, if the up-sampling isperformed in the DCT domain, one has a 2^(N+1)×2^(N+1) DCT block to dealwith, i.e., with one DC component. This is not suitable for operationsthat require the up-sampled DCT block to be in standard MB format, i.e.,four 2^(N)×2^(N) DCT blocks, where N is 4. That is, the up-sampledblocks have the same format or dimensionality as the original blocks,there just are more of them.

The above method of up-sampling in the DCT domain is not suitable foruse in the transcoder described in this invention. In FIG. 11a,up-sampled DCT data are subtracted from DCT data output from the mixedblock processor 1300. The two DCT data of the two blocks must have thesame format. Therefore, a filter that can perform the up-samplingillustrated in FIG. 15C is required. Here, the single 2^(N)×2^(N) block1502 is up-sampled 1540 to four 2^(N)×2^(N) blocks 1550. Because such afilter has not yet been considered and does not exist in the known priorart, an expression for the ID case is derived in the following.

With regard to notation in the following equations, lowercase variablesindicate spatial domain signals, while uppercase variables represent theequivalent signal in the DCT domain.

As illustrated in FIG. 16, C 1601 represents the DCT block to beup-sampled in the DCT domain, and c 1602 represents the equivalent blockin the spatial domain. The two blocks are related to one another throughthe definition of the N-pt DCT and IDCT 1603, see Rao and Yip, “DiscreteCosine Transform: Algorithms, Advantages and Applications,” Academic,Boston, 1990. For convenience, the expressions are also given below.

The DCT definition is $\begin{matrix}{{C_{q} = {z_{q}\sqrt{\frac{2}{N}}{\sum\limits_{i = 0}^{N - 1}{c_{i}{\cos \left( \frac{\left( {{2i} + 1} \right)q\quad \pi}{2N} \right)}}}}},{a\quad n\quad d}} & (13)\end{matrix}$

the IDCT definition is $\begin{matrix}{{c_{j} = {\sqrt{\frac{2}{N}}{\sum\limits_{q = 0}^{N - 1}{z_{q}C_{q}{\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}}}}},{w\quad h\quad e\quad r\quad e}} & (14) \\{z_{q} = \left\{ {\begin{matrix}{\frac{1}{\sqrt{2}};} & {q = 0} \\{1;} & {q \neq 0}\end{matrix}.} \right.} & (15)\end{matrix}$

Given the above, block E 1610 represents the up-sampled DCT block basedon filtering C with X_(u) 1611, and e represents the up-sampled spatialdomain block-based on filtering c with the x_(u) 1621 given by equation(12). Note that e and E are related through a 2N-pt DCT/IDCT 1630. Theinput-output relations of the filtered input are given by,$\begin{matrix}{{{E_{k} = {\sum\limits_{q = 0}^{N - 1}{C_{q}{X_{u}\left( {k,q} \right)}}}};{0 \leq k \leq {{2N} - 1}}},{a\quad n\quad d}} & \text{(16a)} \\{{e_{i} = {\sum\limits_{j = 0}^{N - 1}{c_{j}{x_{u}\left( {i,j} \right)}}}};{0 \leq i \leq {N - 1.}}} & \text{(16b)}\end{matrix}$

As shown in FIG. 16, the desired DCT blocks are denoted by A 1611 and B1612. The aim of this derivation is to derive filters X_(ca) 1641 andX_(cb) 1642 that can be used to compute A and B directly from C,respectively.

As the first step, equation (14) is substituted into equation (16b). Theresulting expression is the spatial domain output e as a function of theDCT input C, which is given by, $\begin{matrix}{e_{i} = {\sum\limits_{q = 0}^{N - 1}{{C_{q}\left\lbrack {\sqrt{\frac{2}{N}}z_{q}{\sum\limits_{j = 0}^{N - 1}{{x_{u}\left( {i,j} \right)} \cdot {\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}}}} \right\rbrack}.}}} & (17)\end{matrix}$

To express A and B in terms of C using equation (17), the spatial domainrelationship between a, b and e is

a ₁ e ₁; 0≦i≦N−1 b _(1−N) e _(i) ; N≦i≦2N−1′  (18)

where i in the above denotes the spatial domain index. The DCT domainexpression for a is given by, $\begin{matrix}{A_{k} = {z_{k}\sqrt{\frac{2}{N}}{\sum\limits_{i = 0}^{N - 1}{a_{i}{{\cos \left( \frac{\left( {{2i} + 1} \right)k\quad \pi}{2N} \right)}.}}}}} & (19)\end{matrix}$

Using equations (17)-(19) gives, $\begin{matrix}{A_{k} = {\sum\limits_{q = 0}^{N - 1}{C_{q}\left\lbrack {\frac{2}{N}z_{k}z_{q}{\sum\limits_{i = 0}^{N - 1}{{\cos \left( \frac{\left( {{2i} + 1} \right)k\quad \pi}{2N} \right)}{\sum\limits_{j = 0}^{N - 1}{{x_{u}\left( {i,j} \right)}{\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}}}}}} \right\rbrack}}} & (20)\end{matrix}$

which is equivalently expressed as $\begin{matrix}{{A_{k} = {\sum\limits_{q = 0}^{N - 1}{C_{q}{X_{c\quad a}\left( {k,q} \right)}}}}{w\quad h\quad e\quad r\quad e}} & (21) \\{{X_{c\quad a}\left( {k,q} \right)} = {\frac{2}{N}z_{k}z_{q}{\sum\limits_{i = 0}^{N - 1}{{\cos \left( \frac{\left( {{2i} + 1} \right)k\quad \pi}{2N} \right)}{\sum\limits_{j = 0}^{N - 1}{{x_{u}\left( {i,j} \right)}{{\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}.}}}}}}} & (22)\end{matrix}$

Similarly, $\begin{matrix}{B_{k} = {\sum\limits_{q = 0}^{N - 1}{C_{q}{\left\lbrack {\frac{2}{N}z_{k}z_{q}{\sum\limits_{i = 0}^{N - 1}{{\cos \left( \frac{\left( {{2i} + 1} \right)k\quad \pi}{2N} \right)}{\sum\limits_{j = 0}^{N - 1}{{x_{u}\left( {{i + N},j} \right)}{\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}}}}}} \right\rbrack}}}} & (23)\end{matrix}$

which is equivalently expressed as $\begin{matrix}{{B_{k} = {\sum\limits_{q = 0}^{N - 1}{C_{q}{X_{c\quad b}\left( {k,q} \right)}}}}{w\quad h\quad e\quad r\quad e}} & (24) \\{{X_{c\quad b}\left( {k,q} \right)} = {\frac{2}{N}z_{k}z_{q}{\sum\limits_{i = 0}^{N - 1}{{\cos \left( \frac{\left( {{2i} + 1} \right)k\quad \pi}{2N} \right)}{\sum\limits_{j = 0}^{N - 1}{{x_{u}\left( {{i + N},j} \right)}{{\cos \left( \frac{\left( {{2j} + 1} \right)q\quad \pi}{2N} \right)}.}}}}}}} & (25)\end{matrix}$

The above filters can then be used to up-sample a single block of agiven dimension to a larger number of blocks, each having the samedimension as the original block. More generally, the filters derivedhere can be applied to any system that requires arithmetic operations onup-sampled DCT data.

To implement the filters given by equations (22) and (25), it is notedthat each expression provides a k×q matrix of filter taps, where k isthe index of an output pixel and q is the index of an input pixel. For1D data, the output pixels are computed as a matrix multiplication. For2D data, two steps are taken. First, the data is up-sampled in a firstdirection, e.g., horizontally. Then, the horizontally up-sampled data isup-sampled in the second direction, e.g., vertically. The order ofdirection for up-sampling can be reversed without having any impact onthe results.

For horizontal up-sampling, each row in a block is operated onindependently and treated as an N-dimensional input vector. Each inputvector is filtered according to equations (21) and (24). The output ofthis process will be two standard DCT blocks.

For vertical up-sampling, each column is operated on independently andagain treated as an N-dimensional input vector. As with the horizontalup-sampling, each input vector is filtered according to equations (21)and (24). The output of this process will be four standard DCT blocks asshown in FIG. 15C.

Syntax Conversion

As stated for the above applications of the transcoder according to theinvention, one of the key applications for this invention is MPEG-2 toMPEG-4 conversion. Thus far, the focus is mainly on the architecturesused for drift compensation when transcoding to a lower spatialresolution and additional techniques that support the conversion tolower spatial resolutions.

However, syntax conversion between standard coding schemes is anotherimportant issue. Because we believe that this has been described bypatent applications already pending, we do not provide any furtherdetails on this part.

Although the invention has been described by way of examples ofpreferred embodiments, it is to be understood that various otheradaptations and modifications can be made within the spirit and scope ofthe invention. Therefore, it is the object of the appended claims tocover all such variations and modifications as come within the truespirit and scope of the invention.

We claim:
 1. A method for transcoding groups of macroblocks of apartially decoded input bitstream, the groups including intra-mode andinter-mode macroblocks, and each macroblock including DCT coefficients,and a motion vector, comprising: mapping the modes of each group ofmacroblocks of the partially decoded input bitstream to be identicalonly if there is an inter-mode macroblock and an intra-mode macroblockin the group, and modifying the DCT coefficients and the motion vectorin accordance with the mapping for each changed macroblock; anddown-sampling each group of macroblocks to generate reduced-resolutionmacroblock for an output compressed bit stream.
 2. The method of claim 1wherein the mode of each changed macroblock is mapped to inter-mode, andthe motion vector and the DOT coefficients of each changed macroblock isset to zero if the partially decoded input bitstream has a relativelysmall amount of motion.
 3. The method of claim 1 wherein the mode ofeach changed macroblock is mapped to inter-mode, and the motion vectorof the changed block is predicted, and the DCT coefficients of thechanged macroblock are converted to inter-mode if the bitstream has arelatively large amount of motion.
 4. The method of claim 1 wherein themode of each changed macroblock is mapped to intra-mode, and the motionvector of the changed macroblock is set to zero, and the DOTcoefficients of the changed macroblock are converted to intra-mode ifthe bitstream has a relatively large amount of motion.
 5. The method ofclaim 1 wherein the down-sampling includes mapping the motion vector toa low-resolution motion vector and further comprising: variable lengthdecoding a compressed bitstream to generate inverse DCT coefficients andthe motion vector of the partially decoded bit stream; inversequantizing the inverse DCT coefficients using a first spatial quantizerto obtain the DOT coefficients; quantizing each reduced-resolutionmacroblock using a second spatial quantizer; and variable length codingeach quantized reduced-resolution macroblock and the low-resolutionmotion vector.
 6. The method of claim 1 further comprising: generating areduced-resolution drift-compensating signal for each down-sampledmacroblock; and adding the reduced-resolution drift-compensating signalto each down-sampled macroblock to compensate for drift in the outputcompressed bitstream.
 7. The method of claim 1 further comprising:generating a full-resolution drift compensating signal for eachdown-sampled macroblock; adding each full-resolution drift-compensatingsignal to each macroblock of the group.
 8. The method of claim 7 furthercomprising: subtracting an inverse quantized signal and up-sampledsignal from an original resolution reference signal to generate thefull-resolution signal.
 9. The method of claim 7 further comprising:subtracting an inverse quantized signal from a reduced resolutionreference signal; and up-sampling the reduced resolution differencesignal to generate the full-resolution signal.
 10. The method of claim 7further comprising: subtracting an inverse quantized and up-sampledsignal from an original resolution reference signal to generate thefull-resolution signal.
 11. The method of claim 1 further comprising:generating a reduced-resolution difference signal for each down-sampledmacroblock; up-sampling each reduced-resolution difference signal to afull-resolution drift-compensation signal; and adding eachfull-resolution drift-compensating signal to each macroblock of thegroup.
 12. The method of claim 1 further comprising: generating afull-resolution difference signal for each down-sampled macroblock; andadding each full-resolution drift-compensating signal to each macroblockof the group.
 13. The method of claim 1 wherein each macroblock includes2^(N)×2^(N) pixels, and the down-sampling further comprises: filteringthe group of 2^(N)×2^(N) macroblocks to generate a single 2^(N)×2^(N)macroblock.
 14. The method of claim 1 wherein the partially decodedinput bitstream is in MPEG-2 format, and the compressed output bitstreamis in MPEG-4 format.
 15. The method of claim 1 wherein the transcodingis performed in a adaptive server of a multimedia content distributionsystem.
 16. The method of claim 1 wherein the transcoding is performedin a transcoder of a home network.
 17. The method of claim 1 furthercomprising: applying a plurality of DOT filters to the DCT coefficientsof each macroblock to generate a plurality of up-sampled macroblocks foreach macroblock, there being one up-sampled macroblock generated by eachfilter, and where the macroblock and up-sampled macroblock has anidentical dimensionality.
 18. An apparatus for transcoding groups ofmacroblocks of a partially decoded input bitstream, the groups includingintra-mode and inter-mode macroblocks, and each macroblock including DCTcoefficients, and a motion vector, comprising: means for mapping themodes of each group of macroblocks of the partially decoded inputbitstream to be identical only if there is an inter-mode macroblock andan intra-mode macroblock in the group, and modifying the DCTcoefficients and the motion vector in accordance with the mapping foreach changed macroblock; and means for down-sampling each group ofmacroblocks to generate reduced-resolution macroblock for an outputcompressed bitstream.